Project Summary/Abstract Clinically associated with chronic, disabling tremors within the 4-12 Hz range, essential tremor (ET) is the most prevalent adult-onset tremor disorder. There is marked heterogeneity in the site of tremor, in the occurrence of non-tremulous symptoms, and in the response to different drugs, alluding to the fact that ET may have several undefined subtypes or is a family of disorders rather than one sole distinguishable disease. Current diagnosis solely depends on subjective clinical measurements, such as the Fahn-Tolosa-Marin Tremor Rating Scale. Once diagnosed, ET can be treated pharmacologically, but for patients unresponsive to medication or with severe tremor, surgical options become viable. Deep brain stimulation (DBS) of the motor nucleus in the thalamus is proven to ameliorate tremor; however, DBS operates in a continuous fashion, leading to adverse effects from unspecific stimulation, rapid battery depletion of the implantable neurostimulator (INS), and impersonalized stimulation paradigms, thus, causing suboptimal clinical outcomes. The current methodology is an inefficient solution especially for patients with tremor, which can dynamically change throughout the day. The objective of this application is to establish physiologic correlates of movement and to characterize the neuromuscular mechanics of tremor throughout the upper extremities using electromyography (EMG) signals in a cohort of humans with ET. This research will lead to a deeper understanding of both the pathological basis of tremor within the extremities, and DBS as well as its mechanisms of action. Our central hypothesis is that wearable sensors, specifically those that measure EMG, can detect correlates of movement that will provide the control signal for responsive DBS in a targeted and personalized manner. Since tremor is paroxysmal and only occurs during movement in ET, responsive DBS only initiates once a movement is detected and then ceases stimulation once movement ends. In Aim 1, we will identify and characterize physiological correlates of tremor throughout the upper limb using EMG signals. In Aim 2, we will establish and clinically validate a responsive DBS system that utilizes physiological correlates of movement to initiate and terminate stimulation in humans with ET. We will initiate responsive DBS based on both the presence of movement and phase of tremor. This research is significant and innovative because it will provide improved tremor suppression through personalized DBS paradigms, reduce adverse effects associated with continuous stimulation, and prolong battery life of the INS, subsequently decreasing the frequency of surgical procedures needed to replace these devices. Additionally, this research has the potential to uncover other uncertainties about ET, including its neuromuscular origin, propagation, and distribution, and to develop an objective measurement of tremor severity, which is an unmet clinical need. Lastly, a sensor-based responsive DBS system can be translatable to other movement disorders, such as Parkinson?s disease.